In the past, the acquisition of traffic information relies on informing initiative of local police and the public, or issuing feedback of a global positioning system (GPS)-based vehicle probe (GVP) and a fixed vehicle detector (VD) device. In recent years, the research and applications of traffic domain use different collection methods and technologies such as vehicle detector, GVP, electronic toll collection (ETC)-based vehicle probe (EVP), and cellular based vehicle probe (CVP) technologies to perform detection of vehicular traffic parameter data.
Mobile users have advantages of the mobile spatial dimension and time dimension. Existing CVP traffic information collection technologies use the mobile phone as the detect tool of traffic information, to collect the transfer signaling between the mobile phone and the network system. And most technologies estimate the vehicle speed on the road through the location of handover events and the location update events, and the time difference between the handover events and location update events, wherein these events may occur when the road users dial/answer the phones. FIG. 1 shows an exemplary schematic view that estimates the vehicle speed on the road by using two handovers caused by a mobile device dialing/answering the phone. In FIG. 1, the mobile device starts to dial/answer the phone at time t0, a handover occurs on the location L1 at the time t1, and another handover occurs on the location L2 at the time t2, thus the vehicle speed on the road is estimated as (L2−L1)/(t2−t1). FIG. 2 shows an exemplary schematic view that estimates the vehicle speed on the road by using two location updates of a mobile device. In FIG. 2, the mobile device starts to move from a location area LA0, an inter-location (inter-LA) update occurs on the location L1 at the time t1, and another inter-location update occurs on the location L2 at the time t2, the vehicle speed on the road is then estimated as (L2−L1)/(t2−t1).
In existing technologies, for example, a technology performs the road test through vehicle equipped with a GPS and a mobile communications module, learns recording location information occurred by call handover, and determines the travel distance between the locations of two handovers; and then the vehicle speed on the road is estimated only by the geographical location of a base station for a mobile phone occurring the handover. Another technology, for example, collects the mobile communication signaling for the users occurring location update at two location areas (LAs); and the vehicle speed on the road is estimated only by the geographical location of a base station for a mobile phone occurring the location update.
Another technology captures the A/Abis interface signal from a global mobile communications system network, analyzes the mobile communication signaling of the location area update and associates with a data mining method to estimate the traffic information of the end-user. Yet another technology is a technology of traffic information of 3G-based mobile communication network signaling. This technique uses the normal location update (NLU) and utilizes the selected handover (SHO) to calculate the vehicle speed on the road.
The traffic information obtained from the above techniques may produce quantity instability of the traffic information. For example, the number of valid samples obtained through two handovers is too small, or the time interval between samples through two location area updates is too long. And these techniques may also cause high cost for vehicle detectors' deployment and operation.
Therefore, under the existing collection policies for the traffic information, how to use the technology with a largest coverage of traffic information collecting, to provide the more accurate traffic information data to the road users, and to reach a driving environment with the better quality is a very important issue.